首页|Peking University Third Hospital Reports Findings in Gastric Cancer (Machine lea rning models to predict submucosal invasion in early gastric cancer based on end oscopy features and standardized color metrics)
Peking University Third Hospital Reports Findings in Gastric Cancer (Machine lea rning models to predict submucosal invasion in early gastric cancer based on end oscopy features and standardized color metrics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Gastric Can cer is the subject of a report. According to news reporting originating from Bei jing, People’s Republic of China, by NewsRx correspondents, research stated, “Co nventional endoscopy is widely used in the diagnosis of early gastric cancers (E GCs), but the graphical features were loosely defined and dependent on endoscopi sts’ experience. We aim to establish a more accurate predictive model for infilt ration depth of early gastric cancer including a standardized colorimetric syste m, which demonstrates promising clinical implication.”
BeijingPeople’s Republic of ChinaAsi aCancerCyborgsEmerging TechnologiesEndoscopyGastric CancerGastroente rologyHealth and MedicineMachine LearningMinimally Invasive Surgical Proce duresOncologySubmucosal InvasionSurgery
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